Using gestures as a means for interfacing with portable devices is becoming commonplace. For example, current Android based phones can control access through sensing and accepting security gestures in place of alphanumeric passwords. Such gestures are typically recognized by analyzing kinematic (motion related) data provided by sensors found in the portable device. Kinematic sensors include accelerometers, gyroscopes, magnetometers, etc.
While analysis of kinematic data profiles can identify some gestures in certain circumstances, other gestures are not readily and/or uniquely identified by their kinematic profiles. By way of example, consider recognition of a “clapping gesture,” where the clapping gesture is accomplished by an operator holding a portable device in the palm of one hand, and clapping both hands together. Perhaps the primary characteristic of this clapping gesture's kinematic profile is that the ends of the profile each tend to have relatively large impulse acceleration/deceleration vectors. However, this profile characteristic could apply to many gestures, such as the operator rapidly waving the portable device in the air.